1. Field of the Invention
The present general inventive concept relates to a method and apparatus to determine a location of a robot (i.e., a method to locate the robot), and more particularly to a method and apparatus to determine the location of a robot using an omni-directional camera on the robot to acquire an omni-directional image.
2. Description of the Related Art
Generally, an omni-directional camera is adapted to acquire an omni-directional image, and can acquire an image of 360° in a vicinity of the camera.
In recent times, the omni-directional camera is mounted to a moving robot in order to recognize a current location of the robot.
A representative example of the above-mentioned omni-directional camera mounted to the moving robot to recognize the location of the robot has been disclosed in Japanese Patent Laid-open No. 10-160463, published on Jun. 19, 1998, which is hereby incorporated by reference. The above-mentioned Japanese Patent Laid-open No. 10-160463 sets a plurality of nodes to specific locations contained in a motion space, moves the moving robot, equipped with the omni-directional camera, to the individual nodes, and stores omni-directional images captured at the individual nodes. Thereafter, the above-mentioned Japanese Patent Laid-open No. 10-160463 moves the moving robot to a specific location, acquires an omni-directional image at the specific location, measures a similarity between the acquired omni-directional image and the pre-stored omni-directional image at each node, and predicts a current location as a starting point of the corresponding node, such that the location of the robot can be recognized.
However, the above-mentioned Japanese Patent Laid-open No. 10-160463 uses a Sum of Absolute Differences (SAD) correlation value to measure the similarity between the current omni-directional image of the robot at the specific location and the pre-stored omni-directional images of each node. The above-mentioned example using the SAD correlation value must directly compare an omni-directional image acquired at each rotation angle of the moving robot with an omni-directional image at each node, such that the number of calculations geometrically increases in proportion to the number of nodes. As a result, it is impossible to recognize the location of the robot in real time, and it is difficult for a user to correctly recognize the location of the robot due to accumulated errors encountered by the increased number of calculations.
In addition, the above-mentioned method cannot recognize the correct location of the robot, and has been designed only to roughly predict which one of the nodes is adjacent to the robot, such that the user has difficulty in recognizing the correct location of the robot.